PCR-like performance of rapid test with permselective tunable nanotrap

Seong Jun Park, Seungmin Lee, Dongtak Lee, Na Eun Lee, Jeong Soo Park, Ji Hye Hong, Jae Won Jang, Hyunji Kim, Seokbeom Roh, Gyudo Lee, Dongho Lee, Sung Yeon Cho, Chulmin Park, Dong Gun Lee, Raeseok Lee, Dukhee Nho, Dae Sung Yoon, Yong Kyoung Yoo, Jeong Hoon Lee

Research output: Contribution to journalArticlepeer-review

6 Citations (Scopus)

Abstract

Highly sensitive rapid testing for COVID-19 is essential for minimizing virus transmission, especially before the onset of symptoms and in asymptomatic cases. Here, we report bioengineered enrichment tools for lateral flow assays (LFAs) with enhanced sensitivity and specificity (BEETLES2), achieving enrichment of SARS-CoV-2 viruses, nucleocapsid (N) proteins and immunoglobulin G (IgG) with 3-minute operation. The limit of detection is improved up to 20-fold. We apply this method to clinical samples, including 83% with either intermediate (35%) or low viral loads (48%), collected from 62 individuals (n = 42 for positive and n = 20 for healthy controls). We observe diagnostic sensitivity, specificity, and accuracy of 88.1%, 100%, and 91.9%, respectively, compared with commercial LFAs alone achieving 14.29%, 100%, and 41.94%, respectively. BEETLES2, with permselectivity and tunability, can enrich the SARS-CoV-2 virus, N proteins, and IgG in the nasopharyngeal/oropharyngeal swab, saliva, and blood serum, enabling reliable and sensitive point-of-care testing, facilitating fast early diagnosis.

Original languageEnglish
Pages (from-to)1520
Number of pages1
JournalNature communications
Volume14
Issue number1
DOIs
Publication statusPublished - 2023 Mar 18

Bibliographical note

Publisher Copyright:
© 2023. The Author(s).

ASJC Scopus subject areas

  • General Physics and Astronomy
  • General Chemistry
  • General Biochemistry,Genetics and Molecular Biology

Fingerprint

Dive into the research topics of 'PCR-like performance of rapid test with permselective tunable nanotrap'. Together they form a unique fingerprint.

Cite this